This 3-day course will focus on the fundamental concepts required for the analysis, modelling and forecasting of time series data using Stata.
This two-day course covers an introduction to Stata and data management. Participants will learn to open datasets in Stata, inspect the data, change data and create variables, create simple graphs and tables, simple programming tools, and save the results and data in Stata and other formats.
The aim of this workshop is to give delegates a practical understanding of the main statistical forecasting tools that are available to support marketing, production, supply chain, and financial decision making.
Our web based ARCH&GARCH modelling with Stata course provides an introduction to Stata’s ARCH/GARCH Commands.
The course will cover: stationary VARs, starting from the basics and tackling more advanced techniques such as dealing with over-parameterisation via Bayesian estimation; non stationary VARs and Johansen approach to cointegration; and structural VARs, and what can be done in EViews 9, will also be explored.
Our web based ARCH & GARCH modelling with Stata course provides an introduction to Stata’s ARCH/GARCH Commands.
Whether you deal with forecasting at a Central Bank, public institution, bank or consultancy firm; or you use forecasting techniques in your research, this is the perfect course to bring you up to date with the latest methods in the forecasting profession.
This one-day course introduces Stata’s capabilities for manipulating survival / time-to-event data, obtaining descriptive and inferential summaries, comparing groups, and constructing regression models for prediction and causal inference.
This course is a primer to machine learning techniques using Stata. Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value form row, large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The training will make use of instructional as well as real-world examples, and will balance evenly theory and practical sessions.
Choosing an appropriate sample size is a common problem and should be given due consideration in any research proposal, as an inadequate sample size invariably leads to wasted resources. This course gives a practical introduction to sample size determination in the context of some commonly used statistical hypothesis tests.